Handheld processing device including medical applications for minimally and non invasive glucose measurements

ABSTRACT

The present disclosure includes a handheld processing device including medical applications for minimally and noninvasive glucose measurements. In an embodiment, the device creates a patient specific calibration using a measurement protocol of minimally invasive measurements and noninvasive measurements, eventually creating a patient specific noninvasive glucometer. Additionally, embodiments of the present disclosure provide for the processing device to execute medical applications and non-medical applications.

INCORPORATION BY REFERENCE TO ANY PRIORITY APPLICATIONS

Any and all applications for which a foreign or domestic priority claimis identified in the Application Data Sheet as filed with the presentapplication are hereby incorporated by reference under 37 CFR 1.57.

FIELD OF THE DISCLOSURE

The present application relates to the field of physiological monitoringdevices. Specifically, the present application relates to the field ofglucometers.

BACKGROUND OF THE DISCLOSURE

Medical device manufacturers are continually increasing the processingcapabilities of patient monitors, specifically of patient monitors thatprocess signals based on attenuation of light by patient tissue. Ingeneral, such patient monitoring systems include one or more opticalsensors that irradiate tissue of a patient and one or morephotodetectors that detect the radiation after attenuation thereof bythe tissue. The sensor communicates the detected signal to a patientmonitor, where the monitor often removes noise and preprocesses thesignal. Advanced signal processors then perform time domain and/orfrequency domain processing to determine measurements of bloodconstituents and other physiological parameters of the patient.

Manufacturers have advanced basic pulse oximeters that determinemeasurements for blood oxygen saturation (“SpO2”), pulse rate (“PR”) andpethysmographic information, to read-through-motion oximeters, toco-oximeters that determine measurements of many constituents ofcirculating blood. For example, Masimo Corporation of Irvine Calif.(“Masimo”) manufactures pulse oximetry systems including Masimo SET® lownoise optical sensors and read through motion pulse oximetry monitorsfor measuring Sp02, PR, perfusion index (“PI”) and others. Masimosensors include any of LNOP®, LNCS®, SofTouch™ and Blue™ adhesive orreusable sensors. Masimo oximetry monitors include any of Rad-8®,Rad-5®, Rad®-5v or SatShare® monitors.

Many innovations improving the measurement of blood constituents aredescribed in at least U.S. Pat. Nos. 6,770,028; 6,658,276; 6,157,850;6,002,952; 5,769,785 and 5,758,644, which are assigned to Masimo and areincorporated by reference herein. Corresponding low noise opticalsensors are disclosed in at least U.S. Pat. Nos. 6,985,764; 6,088,607;5,782,757 and 5,638,818, assigned to Masimo and incorporated byreference herein.

Masimo also manufactures more advanced co-oximeters including MasimoRainbow® SET, which provides measurements in addition to Sp02, such astotal hemoglobin (SpHb™), oxygen content (SpCO™), methemoglobin(SpMet®), carboxyhemoglobin (SpCO®) and PVI®. Advanced blood parametersensors include Masimo Rainbow® adhesive, ReSposable™ and reusablesensors. Masimo's advanced blood parameter monitors include MasimoRadical-7™, Rad87™, and Rad-57™ monitors as well as Pronto and Pronto-7spot check monitors.

Innovations relating to these more advanced blood parameter measurementsystems are described in at least U.S. Pat. Nos. 7,647,083; 7,729,733;U.S. Pat. Pub. Nos. 2006/0211925; and 2006/0238358, assigned to CercacorLaboratories of Irvine, Calif. (“Cercacor”) and incorporated byreference herein.

Such advanced pulse oximeters, low noise sensors and advanced bloodparameter systems have gained rapid acceptance in a wide variety ofmedical applications, including surgical wards, intensive care andneonatal units, general wards, home care, physical training, andvirtually all types of monitoring scenarios.

SUMMARY OF THE DISCLOSURE

The present disclosure includes a handheld processing device includingmedical applications for minimally and noninvasive glucose measurements.In an embodiment, the device includes a minimally invasive glucosebiosensor (“strip reader”). Manufacturers have developed strip readersin various embodiments for decades primarily for the measurement ofglucose. Such strip readers often employ disposable strips that includean enzyme electrode and mediator compound, where the mediator compoundmoves electrons between the enzyme and the electrode to result in ameasurable electrical current at the electrode when glucose is present.The strip reader measures this current when the disposable strip isinserted and then determines glucose values corresponding to thereceived current. Diabetics, for example, often rely on strip readers toprovide minimally invasive measurements of their glucose levels. Inshort, a user often pricks a finger and deposits one or more droplets ofblood on a test strip. The user then inserts the blood carrying stripinto a strip reader, which in turn uses the measurable electrical signalto determine glucose measurements for the user.

In an embodiment, the device also includes a noninvasive glucosemeasurement solution. For example, the device communicates with anoninvasive optical sensor to receive signals responsive to theattenuation of various wavelengths of light by a user's tissue. Thedevice processes these signals to determine current glucose measurementsfor the user.

As is widely understood by one of ordinary skill in the glucosemeasurement arts, noninvasive determination of glucose throughprocessing absorption signals is complicated and often difficult toaccurately perform over large patient populations. In an embodiment ofthe present disclosure, patient specific calibration of the deviceoccurs through information exchanges between the device, with its theminimally invasive and noninvasive measurements, and a centralizedcomputing system. For example, the device communicates with one or moreremote computing centers to upload patient measurements and download,for example, patient specific calibrations. Through the interaction ofthe centralized computing system and many processing devices asdisclosed herein, the manufacturer collects vast amounts of anonymousphysiological data associating minimally invasive measurements andnoninvasive measurements. These associations can then produce reliablecalibration data specific to a user and across large user populations.For example, in certain embodiments, uploads of thousands to hundreds ofthousands of measurements per week create data resources unobtainablethrough traditional clinical testing environments.

Additional embodiments of the present disclosure include the processingdevice including medical related functions and non-medical relatedfunctions that may share common resources. Advantageously, theprocessing device includes a priority mechanism so as to prevent themedical related functions from competing with the non-medical relatedfunctions for the common resources during critical time periods. Thesecritical time periods may be indicated by triggering events. Inparticular, a triggering event indicates to the system that the medicalrelated functions have resource priority. This priority may be, forexample, exclusive access to and use of displays, alarms, controls,communications and processing power so as to make time critical patienthealth and risk assessments and output those assessments in a timelymanner to a healthcare provider. In an embodiment, the physiologicalmonitor is integrated with a smart phone so as to advantageously allowflexible communications between the physiological monitor and a broadrange of external information sources and information receivers. Thesecommunications occur over any of a wide variety of communication links,both wired and wireless. Wireless communications may include, but arenot limited to, GPS, cellular networks, Wi-Fi and Bluetooth to name afew, so as to connect to the Internet, telephone systems and other widearea networks. Wired communications may include, but are not limited to,USB. A broad range of third-party applications are available for thesmart phone, also providing increased functionality to the physiologicalmonitor.

In additional embodiments, the processing device may include thealteration of smart phone processing systems to manage physiologicaldata. For example, in some embodiments, a processing board or card maybe included within an existing smart phone technology. The board or cardmay include one or more signal processors and associated memory, I/O,and the like to provide measurement or other physiological data toapplications executing on traditional smart phone processingenvironments. In an embodiment, the communication may be wired orwireless and the board or card may be internal or external. In somecases, the board may be a clip-on cartridge or other smart phoneextension that electronically and/or physically mates with the housingand processing of the smart phone.

In an embodiment, a monitoring board may be physically integrated andattach to a connected sensor. In another embodiment, the monitoringboard may mechanically and/or electrically mate with the smart phone. Inthis embodiment, the sensor may include the monitoring board, which thencommunicates with a smart phone, or portions of the monitoring board maybe shared between an external sensor and the smart phone. In astandalone embodiment, the monitoring board and the sensor may be anintegrated unit or a unit with an attached sensor, where the unitcommunicates with smart phone or other digital processing devices.

For purposes of summarizing the invention, certain aspects, advantagesand novel features of the invention have been described herein. Ofcourse, it is to be understood that not necessarily all such aspects,advantages or features will be embodied in any particular embodiment ofthe invention.

For purposes of summarizing the invention, certain aspects, advantagesand novel features of the invention have been described herein. Ofcourse, it is to be understood that not necessarily all such aspects,advantages or features will be embodied in any particular embodiment ofthe invention.

BRIEF DESCRIPTION OF THE DRAWINGS

The following drawings and the associated descriptions are provided toillustrate embodiments of the present disclosure and do not limit thescope of the claims.

FIG. 1 illustrates a simplified perspective view of a processing systemaccording to an embodiment of present disclosure, including a processingdevice, a noninvasive sensor, a cable providing communication betweenthe device and the sensor, and a disposable strip.

FIG. 2 illustrates a simplified perspective view of the processingdevice of FIG. 1 , according to an embodiment of present disclosure.

FIGS. 3A-3F illustrate simplified top, front, rear, left, right, andback views of the processing device of FIG. 1 , according to anembodiment of present disclosure.

FIGS. 4A-4B illustrate simplified exploded views of the processingdevice of FIG. 1 , according to an embodiment of present disclosure.

FIG. 5 illustrates a simplified hardware/software block diagram of theprocessing system of FIG. 1 , according to an embodiment of presentdisclosure.

FIG. 6 illustrates a simplified data flow diagram between applicationsof the processing device of FIG. 1 and remote computing servers,according to an embodiment of present disclosure.

FIG. 7 illustrates a simplified measurement process according to anembodiment of the present disclosure.

FIG. 8 illustrates a simplified minimally invasive strip measurementprocess according to an embodiment of the present disclosure.

FIG. 9 illustrates a simplified noninvasive sensor measurement processaccording to an embodiment of the present disclosure.

FIGS. 10-19 illustrate exemplary user interfaces of the processingdevice of FIG. 1 , according to various embodiments of the presentdisclosure. Specifically, FIG. 10 illustrates an exemplary test resultinterface, FIG. 11 illustrates an exemplary bar graph interface, FIGS.12A-12B illustrate exemplary result and trend interfaces, FIGS. 13A-130illustrate exemplary trend interfaces, FIGS. 14A-14B illustrateexemplary calibration protocol interfaces, FIGS. 15A-15D illustrateexemplary alarm interfaces, FIGS. 16A-16C illustrate exemplaryinstructive interfaces, FIG. 17 illustrates an exemplary applicationsinterface, FIGS. 18A-18B illustrate exemplary events interfacesincluding a food flag interface, and FIGS. 19A-19B illustrate exemplarypriority interfaces.

FIG. 20 illustrates a simplified block diagram of a priority modeprocessing device according to an embodiment of the present disclosure.

FIG. 21 illustrates a simplified block diagram of a priority modeprocessing device according to an embodiment of the present disclosure.

FIGS. 22A-22D illustrate priority mode glucometers according toembodiments of the present disclosure showing connected and disconnectedsensors and inserted and removed test strips, respectively.

FIG. 23 illustrates a simplified block diagram of priority modeprocessing device utilizing a KVM switch for priority control accordingto an embodiment of the present disclosure.

FIG. 24 illustrates a simplified block diagram of priority modeprocessing device utilizing an activated medical app for prioritycontrol according to an embodiment of the present disclosure.

FIG. 25 illustrates a simplified block diagram of priority modeprocessing device utilizing separate virtual machines for prioritycontrol according to an embodiment of the present disclosure.

FIG. 26 illustrates a simplified block diagram of priority modeprocessing device utilizing a cell phone operating system that issuspended in favor of a medical system application when a sensor orstrip is detected according to an embodiment of the present disclosure.

FIG. 27 illustrates a simplified block diagram of priority modeprocessing device having dual-booted operating systems according to anembodiment of the present disclosure.

FIG. 28 illustrates a simplified block diagram of priority modeprocessing device having double-sided device functionality according toan embodiment of the present disclosure.

FIG. 29 illustrates a simplified block diagram of priority modeprocessing device running a single medical application in lieu of amulti-task normal operating mode according to an embodiment of thepresent disclosure.

FIG. 30 illustrates a simplified exploded view of an expanded smartphone including internally integrated medical processing capabilityaccording to an embodiment of the disclosure.

FIG. 31 illustrates various exemplary connectable cartridges for anexpanded smart phone to provide medical processing capabilities,according to an embodiment of the disclosure.

FIGS. 32-34 illustrate medical processing cartridges as separate unitscommunicating to create an expanded smart phone according to embodimentsof the disclosure.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

The present disclosure includes a handheld processing device includingmedical applications for minimally and noninvasive glucose measurements.In an embodiment, the device creates a patient specific calibrationusing a measurement protocol of minimally invasive measurements andnoninvasive measurements, eventually creating a patient specificcalibrated noninvasive glucometer. Additionally, embodiments of thepresent disclosure provide for the processing device to execute medicalapplications and non-medical applications. In an embodiment the medicalapplications may advantageously relate to the foregoing patient specificnoninvasive glucometer. Such applications may advantageously includemeasurement applications, tracking applications including dietapplications to track caloric intake and/or caloric usages, calendaring,and other glucose management applications. In other embodiments, othermedical applications may monitor respiration, blood pressure, otherblood parameters, combinations of parameters, wellness measurements orthe like. The nonmedical applications may include communicationprotocols, connectivity protocols, smart phone and cellphonecapabilities, entertainment applications, productivity applications, orvirtually any application available on today's existing sophisticatedsmart phones.

In other embodiment's, the processing device generates patient specificcalibrations through information exchanges between the device and acentralized computing system. For example, the device may uploadmeasurement information to one or more remote computing data centersover wireless, mobile, Wi-Fi, wired, or other networks and downloadpatient specific or other updated calibrations. Advantageously, throughthe upload of measurement data, the manufacturer may collect anonymousclinical data that can be used to create ever more accurate noninvasivemeasurements.

According to further embodiments, the processing device includes medicaland nonmedical applications that may share common resources.Advantageously, the processing device includes a priority mechanism soas to prevent the medical related functions from competing with thenon-medical related functions for the common resources during criticalor otherwise medically relevant time periods.

In still further embodiments of the present disclosure, such processingdevices as disclosed herein may be incorporated into existing smartphone processing platforms.

To facilitate a complete understanding of the invention, the remainderof the detailed description describes the invention with reference tothe drawings, wherein like reference numbers are referenced with likenumerals throughout.

FIG. 1 illustrates a simplified perspective view of a processing system100 according to an embodiment of present disclosure, including aprocessing device 102, a noninvasive sensor 104, an associated cable 106providing communication between the device 102 and the sensor 104, and adisposable glucose strip 108. The processing device 100 comprises ahandheld housing including an integrated touch screen 110, one or moreinput keys 112, and an integrated camera 113 preferably capable of photoand/or video capture. In an embodiment, the screen 110 rotates as thedevice 102 is held in differing orientations; however, the preferredorientation is for use is the landscape orientation as illustrated inFIG. 2 .

FIG. 1 also illustrates additional features of the device 102. Forexample, the device 102 includes along a side thereof an integratedstrip reader, including a strip input cavity 114, and a power button116. Along another side, the device 102 includes a noninvasive sensorcable input port 120 (FIG. 3E) and volume controls 122 (FIG. 3E). Alongyet another side, the device 102 includes a headphone jack 124, a microSD card reader input cavity 126, a micro HDMI connector 128, a Micro USBconnector 130 configured for, for example, data transfer and batterycharging, and an optional audio transducer, such as, for example, aspeaker 132. Along a back side thereof, in an embodiment, the processingdevice 102 includes a camera 134 (FIG. 3F) and LED flash 136 (FIG. 3F).

As disclosed, the device 102 communicates with a noninvasive opticalsensor 104, such as, for example, a clothespin style reusable opticalsensor, in some mechanical respects similar to those employed instandard pulse oximetry. The sensor 104 may also include advancedfeatures, such as those disclosed in U.S. Pat. No. 6,580,086, and U.S.Pat. Pub. No. 2010-0026995, on Feb. 4, 2010, titled “Multi-stream SensorFor Noninvasive Measurement of Blood Constituents,” each of which isincorporated by reference herein. Specifically, the sensor 104 includesa plurality of emitters emitting light of a variety of wavelengths toform a light source. A plurality of detectors detect the light afterattenuation by a digit of the patient. A plurality of temperaturesensors and one or more memory devices may also be incorporated into thesensor 104. These devices communicate their information to the device102 through the cable 106.

In general, the user interacts with the processing device 102 to obtainglucose measurements. The user may input the disposable strip 108 with ablood sample and the device 102 will, if not already, electronicallywake up a medical application and display glucose measurements obtainedfrom the strip reader. The user may also apply the sensor 104 to a digitand upon activating a “test” input, the device 102 may process thedetector signals and display glucose measurements derived from thereceived signals.

Although disclosed with respect to the embodiment shown in FIG. 1 , anartisan will recognize from the disclosure herein alternative oradditional functionality, user interaction mechanisms, and the like. Forexample, the device housing may be shaped to ergonomically fit a user'shand, may include more or less input mechanisms including, for example,a connectable or slideout keyboard, a pointing device, speechrecognition applications, or the like. Moreover, the sensor 104 maywirelessly communicate with the device 102. The device 102 maycommunicate with an external strip reader or other medical sensors ordevices.

FIGS. 3A-3F illustrate simplified top, front, rear, left, right, andback views of the processing device 102 of FIG. 1 , according to anembodiment of present disclosure.

FIGS. 4A-4B illustrate simplified exploded views of the processingdevice 102 of FIG. 1 , according to an embodiment of present disclosure.As shown, the device 102 includes the touch screen 110 housed in anupper housing 400, a main frame 402, a main board 404, a battery 406 anda rear housing or casing 408. In an embodiment, the touch screen 110comprises a 5.6″ LED backlit LCD with 1280×800 pixel resolution with262,144 colors and a viewing angle of 179 degrees, although an artisanwill recognize from the disclosure herein a wide variety of possibledisplay devices.

FIG. 5 illustrates a simplified hardware block diagram 500 of theprocessing system 100 of FIG. 1 , according to an embodiment of presentdisclosure. As shown in FIG. 5 , the processing device 102 includes aplurality of processors, including a front end processor 502 configuredto execute a number of processes, including medical processes and signalprocessing processes, a coprocessing DSP 504 configured to execute anumber of calculators and assist the front end 502 in intensivecalculation processes, and an applications processor 506, configured toexecute a medical applications and more traditional smart phoneapplications, including, for example, cell phone, internet,entertainment, and productivity applications. In an embodiment, thefront end 502 comprises an OMAP style processing system available fromTexas Instruments, generally comprising an ARM9 processor and one ormore digital signal processors or specialized co-processors. In anembodiment, the front end 502 may comprise an OMAP L138 processorsystem. In an embodiment, the coprocessor 504 comprises a Snowbird styledigital signal coprocessor from Analog Devices. In an embodiment, theapplications processor 506 comprises a Linux processor from Samsungincluding a Cortex-A9 ARM processor.

Although disclosed with reference to specific processing technologies,an artisan will recognize from the disclosure herein that the processorcould comprises a single processing device, more or less than three (3)processing devices, a wide variety of hardware and/or softwaresolutions, other processing devices, or the like.

The front end 502 communicates with the sensor 104 components toaccomplish the noninvasive measurements of the present disclosure. Forexample, the front end 502 communicates with one or more light sources510 to irradiate a digit 512 of a wearer of the sensor 104. A pluralityof photodetectors 514 receive the irradiated light after attenuation bythe tissue of the digit 512. In an embodiment, the detectors 514comprises four (4) detectors logarithmically spaced apart along an axisparallel to a long axis of the digit 512, the detectors 514 optionallymounted on an actuator 516. In an embodiment, the actuator 516 moves thedetectors in a predefined motion to create an active pulse technology,similar to that disclosed in U.S. Pat. No. 5,638,816, titled “ActivePulse Blood Constituent Monitoring,” or in U.S. Pat. Prov. App. Ser. No.61/486,689 filed on May 16, 2011, titled “Personal Health Device,” eachof which is incorporated by reference herein. The detectors 514 outputtheir respective channels of data, or signals to the front end 502 forprocessing. In addition to the light source 510 and the detectors 514,the front end 502 may advantageously communicate with a plurality oftemperature sensors 518, and one or more memories 520. In an embodiment,the front end 502 communicates with a temperature sensor 518 configuredto supply an indication of the temperatures of the emitting LEDs of thelight source 510, a temperature sensor 518 configured to supply anindication of the temperature of the tissue being monitored, and atemperature sensor 518 configured to supply and indication of thetemperature of the detectors 514.

The front end processor 502 also communicates extensively with thecoprocessor 504 over, for example, a dedicated high speed connection. Inan embodiment, the medical application algorithms and mathematics thatgenerate noninvasive measurements may be regarded as highly sensitiveinformation. Thus, the communication between the processors 502 and 504may advantageously be encrypted to ensure their sensitivity isappropriately guarded.

The front end processor 502 additionally communicates with theapplications processor 506. In an embodiment, determined measurementvalues are forwarded to the applications processor 506, where, forexample, medical applications use the data to present information to theuser on the display 110. The applications processor 506 alsocommunicates with the strip reader 520. In an embodiment, the stripreader 520 comprises a commercially available OEM strip reader from, forexample, Nova Medical. In an embodiment, the strip reader includes acurrent detector, or reader 522 and a controller 524 for determiningfrom an inserted strip 108, minimally invasive glucose measurements. Thereader 520 forwards calculated measurements to the applicationsprocessor 506, where, for example, medical applications use the data topresent information to the user on the display 110.

As disclosed in the foregoing, the applications processor 506 executes awide variety of medical applications and smart phone or otherapplications, any of which may access wireless communicationfunctionality, including Wi-Fi, 3 and/or 4 G or higher connectivity,Bluetooth, Ant, near field communication (“NFC”), cellular, or otherwireless connectivity, SD card functionality, HDMI functionality, imageand video data, and user input.

Although disclosed with reference to the specific embodiment of FIG. 5 ,an artisan will recognize from the disclosure herein other hardwareand/or software configurations for accomplishing the desiredfunctionality, including, for example, custom semiconductors,controllers, processors, or the like for performing individual or setsof functions.

FIG. 6 illustrates a simplified data flow diagram between applicationsof the processing device 102 of FIG. 1 and remote computing servers,according to an embodiment of present disclosure. As shown in FIG. 6 , ahealth monitor 602 including, for example, the glucometer as disclosedabove, communicates data with a number of other processing centers,including a number of applications 604 and at least one remote dataprocessing center 606. As shown in FIG. 6 , the health monitor 602 maycommunicate with one or more of the following sensors, devices, ortechnologies: ECG and/or EEG sensors or devices, respiration sensors ordevices, including acoustic sensors such as those commercially availablefrom Masimo, sleep apnea sensors or monitors, invasive technologies suchas the above discussed strip reader or other invasive technologies,blood pressure sensors or devices, temperature sensing technologies,drug testing sensors or devices, depth of consciousness sensors ordevices, and other patient monitoring devices. As shown in FIG. 6 , thisinteraction with the monitor 602 advantageously allows the monitor touse the information in its medical calculations, as well provide thatinformation further to various applications 604 and the remoteprocessing center 606.

The applications 604 may include a wide variety of applicationsincluding, for example, the health applications disclosed herein, orsimilar applications, phone, business, entertainment including video,music, pictures, and the like, productivity, social, games, utilityapplications and the like, many of which can be associated with today'ssmart phone technologies. In an embodiment, the applications may includesome combination or all of the applications disclosed in U.S. Pat. App.Pub. No. 2011-0082711, filed on Apr. 7, 2011, titled, “Personal DigitalAssistant or Organizer for Monitoring Glucose Levels,” incorporated byreference herein.

The remote data processing center 606 communicates with the healthmonitor 602 and the applications 604 to store and process vast amountsof data, including for example, minimally and noninvasive glucosemeasurements for patient specific and population calibration processing,electronic medical records (“EMR”) and electronic health records(“EHR”), or the like. In an embodiment, the remote data processingcenter 606 may also perform device management functions, including, forexample, maintenance of software and firmware executing on theprocessing device 102, and measurement credit processing, such as themeasurement credit processing disclosed in U.S. Pat. App. Pub. No.2011-0172498, filed Jul. 14, 2011, titled “Spot Check Monitor CreditSystem,” incorporated by reference herein disclosing, in general,embodiments for managing spot check pricing for medical instruments.

As will be understood by an artisan from the disclosure herein, the dataprocessing center 606 may comprise one or many physical and/or logicallocations, servers, systems, or the like, accessible by any of a largenumber of connectivity options. It may be geographically distributed,may have mirrored or backup sites, may be one or many processing deviceor the like.

Communication between the device 102 and the remote data processingcenter 606 advantageously benefits all parties. For example, the user bysharing their measurement data in a confidential and/or anonymous mannerprovides valuable data to, for example, the manufacturer. The amount ofthis data could be staggering when compared with the amount of datatraditionally gathered during clinical trials. Supplementing actualclinical trial information with valuable uploaded information provides acost effective and timewise practical solution to very costly clinicaltrial studies. In return, the user receives from the remote processingcenter patient specific calibration data ensuring the most accurateassociation of absorption-derived data and output measurement data. Forexample, oximeters and cooximeters use clinical data to map noninvasivemeasurement results to clinically-determined output measurements. Thismapping is often referred to as “calibration.” With the presentdisclosure, the clinical data is vastly supplemented with user datacreating much more accurate calibrations, and specifically,user-specific calibrations. These calibrations are downloaded to themonitor 602.

For example, because of many challenges associated with the accuratenoninvasive optical absorption-based glucose measurements, variabilityin calibrations between subjects can be high, in some cases too high forglobal calibrations to accurately support large user populations. Thus,in an embodiment of the present disclosure, the processing device 102improves its calibration for a specific user through communication withthe data processing center 606. In an embodiment, qualification for useof the device 102 to provide noninvasive glucose measurements isdependent upon the interaction with the data processing center 606. Forexample, FIG. 7 and its disclosure relates to a protocol for qualifyingor preparing a processing device 102 for use noninvasively.

FIG. 7 illustrates a simplified measurement process or protocol 700,according to an embodiment of the present disclosure. In an embodiment,the protocol 700 includes Step 702 where a patient qualifies fornoninvasive glucose measurements. Some research suggests that onlyaround seventy percent (70%) of possible patients qualify fornoninvasive glucose measurements. Disqualification can be the result ofmany things, in particular optical density coupled with poor digitperfusion. Thus, in an embodiment, the device 102 may drive the lightsource 510 of the sensor 104 and receive optical absorption data. Basedon the signal strength and/or quality of the data, the device 102 mayrequest the user place the sensor on a different digit. Reasons for poorperformance include finger thickness, pigmentation, perfusion,temperature, or the like. In some cases, the device 102 determines oneor several ideal digits through the testing of each one for noninvasivemeasurements. In other embodiment, once the device 102 finds asufficient digit, it recommends use of that one. Through, for example,the determination of potential signal strength of the optical signalsreceived from the sensor 104, the device 102 may pre-qualify a user as acandidate for noninvasive glucose measurements. Full qualification maynot occur at all or at least until much of the protocol 700 iscompleted.

The protocol 700 also includes Step 704, where the device 102 enters acalibration phase. During calibration, many invasive measurements, suchas strip measurements are taken. In an embodiment, during this step,noninvasive measurements are not displayed as they are not sufficientlycalibrated for a particular user. In an embodiment, about twenty (20) toabout sixty (60) invasive measurements are performed during up to aboutthirty (30) days. In an embodiment, the user takes noninvasivemeasurements with each of the invasive measurements in order toassociate instrument readings with invasive results. While providing aguideline for the calibration process, the protocol is not meant to belimited thereby. The device 102 uses a certain number of measurementsover a certain time to develop a reliable calibration. Some users willenthusiastically provide multiple measurements, perhaps manymeasurements per day. Other will only provide a minimal number, such asone or two measurements per day. The calibration process length will belonger for the latter than it will for the former.

In an embodiment, because of the difficultly associated with crosssubject variability in the calibrations process, e.g., the process ofmapping noninvasive instrument readings with glucose values, in anembodiment, the device originates with a general calibration or in somecases, no calibration at all. The user begins taking measurements anduploads the measurements to the data processing center 606. Aftersufficient measurements, such as, for example, about twenty (20) toabout one hundred (100) or so over about twenty (20) to forty five (45)days, the data processing center 606 will begin to see a convergence ofthe patient-specific calibration. In one sense, the mappings will beginto stabilize. For example, over that time period it is anticipated thatthe about minimums and about maximums start to fill in with patientspecific correlations between noninvasive measurements and invasivemeasurements and the mapping functions will start to look more similarto the previous mappings. When sufficient convergence and/orstabilization occurs or begins to occur, the center 606 may download thepatient-specific calibration to the device 102.

The measurement process 700 also includes Step 706, where the device 102enters a verification phase. During verification, invasive measurements,such as strip measurements are taken, to ensure that the calibration hasconverged. For example, in an embodiment, the data processing center 606has downloaded a patient specific calibration to the device 102.Accordingly, the device generates optical absorption data, associatedstrip readings, and from its downloaded calibration, noninvasive glucosemeasurements. These now three associated pieces of data canadvantageously be uploaded to the data processing center 606 and thenewly found noninvasive glucose measurements can be verified as beingaccurate according to the expected and downloaded patient-specificcalibration. Thus, advantageously, in Step 706, the protocol proves orverifies that the device 102 is generating acceptable and accuratenoninvasive glucose measurements and otherwise functioning properly. Inan embodiment, the data processing center 606 reduces the data storagerequirements for the device 102 by storing the data associated with thecalibration protocol remote from the device 102. In other embodiments,the process 700 may occur entirely within device 102, or with otheraccess to remote data systems.

In an embodiment, during Step 706, verification, noninvasivemeasurements are not displayed as they may still be in need of furthercalibration for a particular user. In an embodiment, about one (1) toabout two (2) invasive measurements should be performed per day for upto about five (5) days. In an embodiment, the user takes noninvasivemeasurements with each of the invasive measurements in order toassociate instrument readings with invasive results.

The protocol 700 also includes Step 708, where the device 102 enters asustaining or maintenance phase. During this phase, invasivemeasurements, such as strip measurements are taken, to ensure thecalibration has not drifted from previous calculations. In anembodiment, during this step, noninvasive measurements are displayed asfrequently as they are taken. In an embodiment, invasive measurementscan be about one (1) week apart.

The measurement process 700 also includes Step 710, where the device 102compares current noninvasive measurements to determine whether suchmeasurements are outside expectations. For example, in an embodiment,the device 102 uploads measurement data to the processing center 606. Asdisclosed above, such information may advantageously include noninvasiveglucose measurements and corresponding optical absorption data setsmeasured by the sensor 104. The data processing center 606 mayadvantageously use the glucose measurements alone, or with additionalphysiological information about the user, to retrieve more generalizedor stored optical absorption data sets associated with that measurement.For example, when the device 102 measures 125 mg/dL glucose and uploadsthat to the center 606, the center 606 may advantageously retrievestored optical absorption data sets associated with 125 mg/dL. Thesestored sets may be idealized, generalized, specific for the user, orcombinations of the above. The stored data sets are then statisticallycompared to the uploaded data set from the device 102 associated withits measurement of, for example, 125 mg/dL glucose. The statisticalcomparison may be a Gaussian comparison or other statistical comparisonsthat provide an indication of how similar are the data sets, e.g., thestored data set and the uploaded data set, each associated with asimilar or same glucose measurement, in this case, 125 mg/dL glucose.When the sets begin to be sufficiently dissimilar, the center 606 mayinform the device 102 that the measurements are no longer withinexpectations and the device should be recalibrated. In an embodiment,recalibration can be a full recalibration or a partial recalibration orsimply a restart of one of the other phases.

FIG. 8 illustrates a simplified minimally invasive strip measurementprocess 800 according to an embodiment of the present disclosure. Theprocess 800 includes Step 802, where a strip with the user's blood isinserted into the strip reader. In Step 804, a medical application wakesup and takes priority of any necessary shared resources in theprocessing device 102. The reader determines an output and forwards theoutput measurement to the medical application. In Step 806, theapplication may determine to optionally display the result, particularlywhen the result indicates an abnormal condition or a trend is movingtoward an abnormal condition. In Step 808, the application determineswhether a noninvasive measurement is desired, such as, for example, whenthe device 102 is performing a calibration or other phase, where, forexample, timewise-commensurate minimally and noninvasive measurementsare desired. In Step 810, the application may prompt the user to begin anoninvasive sensor measurement process, such as process 900, disclosedherein. In Step 812, the application may determine to optionally displaythe minimally invasive result, particularly if the result was notdisplayed above. In an embodiment, the application may display bothresults, only one result, a result in which there is an associatedhigher confidence, or a combination of the results. In Step 814, themeasurement values are uploaded to one or more remote data processingcenters. Other information may also be uploaded, such as, for example,spot check purchasing information, version information, demographicinformation, device information, use information for the device, thesensor, and/or the cable, or the like. In Step 816, the application maydetermine that the center is ready to download information to the device102. For example, the center may have updated calibration informationbased on current or previous uploads, other users uploads, thecalibration may be beginning or actually stabilizing and/or converging,or the like. Moreover, the center may download spot check purchasinginformation, other application information, or the like.

FIG. 9 illustrates a simplified noninvasive sensor measurement process900 according to an embodiment of the present disclosure. The process900 includes Step 902, wherein if not already, the user wakes up themedical application. In Step 904, the user attaches the sensor 104 to adigit and activates a test input, such as a button on the touch screenof the device 102. In Step 906, the device 102 processes the detectorsignals to determine noninvasive glucose measurement values. In Step908, the application determines whether the device 102 has beensufficiently calibrated with invasive measurements. If not, theapplication requests in Step 910 that an invasive measurement be taken.In Step 912, even when the device 102 is sufficiently calibrated,additional less frequent invasive measurements may be recommended toensure accurate noninvasive performance. In Step 914, the applicationdetermines whether the processed noninvasive measurement is withinexpectations. In an embodiment, the device may include limits for itscalibration, may include data sets for certain calibrations, may includeconfidence indicators for particular measurements based on, for example,the optical signal processing, or the like to understand whether currentmeasurements are outside expectations. In Step 916, the applicationdisplays, when appropriate, the noninvasive measurements. In Step 918,the measurement values and/or other information are uploaded to one ormore remote data processing centers. In Step 920, the application mayreceive information from the data center.

FIGS. 10-19 illustrate exemplary user interfaces of the processingdevice of FIG. 1 , according to various embodiments of the presentdisclosure. As shown in many of the user interfaces, familiar smartphone icons may be used such as, for example, battery power, time,connectivity such as Bluetooth or Wi-Fi, 3 G or higher connectivity,cellular connection signal strength such as increasing bars, and thelike. Additionally, in the case of a spot check device, the device mayinclude a readily identifiable indicator for the amount of measurementsreaming or otherwise paid for. For example, FIG. 10 shows a “220” with agreen check to indicate the user has prepaid or otherwise received 220spot check measurement credits.

Moreover, FIG. 10 illustrates an exemplary test result interface, whichmay advantageously show the available scale, the severity at each end ofthe scale in alternating colors, such as, for example, green when themeasurements are normal, yellow on each side as they move away fromnormal and red where measurements are abnormal.

FIG. 11 illustrates an exemplary bar graph interface which may, forexample, show readings during different activities for a particular timeperiod. For example, FIG. 11 shows a collection of readings before andafter meals, and numerically provides a combination of those readings.In an embodiment, the combination is a simple average. In otherembodiment, the combination may be more statistically sophisticatedand/or appropriately weight confidence indications associated withparticular readings. In an embodiment, the scale at the bottom of theinterface shows the time period of the combination, such as, forexample, the simple average. In this case, the user has selected toaverage 14 days. As shown, the user could select days, months, or years,and then slide the bar for a numerical value of the same, and theprocessing device 102 would combine the stored measurement values overthe corresponding time for display in similar fashion. Other activitiesaround which one may wish to summarize measurement values may includeexercise, snacks, specific dietary intake, times of day or week, or thelike.

FIGS. 12A-12B illustrate exemplary result and trend interfaces. Forexample, FIG. 12A may show basic information for noninvasivemeasurements, along with a trend showing readings over time. The trendmay advantageously include flags for entered activities, may highlightabnormal or trending toward abnormal behaviors. In the particularembodiment shown, the round points indicate noninvasive measurements andthe triangle points indicate strip or otherwise invasive measurements.Moreover, the trend may be selectable to review information availablefor the selected point in time. An activity log may also be shown. FIG.12B may show similar basic information for invasive measurements, andswitch the location and/or color to ensure a user can readily recognizethe difference between the display of invasive and noninvasive values.Other icons or text may also be used to distinguish the measurements,such as, for example a blood droplet and/or triangle to indicate a stripmeasurement being displayed.

FIGS. 13A-13D illustrate exemplary trend interfaces. FIG. 13Aillustrates an exemplary single trend of glucose measurements. In anembodiment, the trend may show both invasive and noninvasivemeasurements or may include trend lines for each type. Also, the trendline timeframe, or displayed time period, may be configurable through,for example, a pinch or dual finger parting to respectively shorten orlengthen the time period. FIG. 13B illustrates exemplary trends ofmultiple parameters, in this case, glucose and blood pressure, over thesame time period so that, for example, a caregiver can readily recognizeor identify how events in the multiple physiological parameters affect aparticular parameter. For example, the user could readily review whetherspikes or falls in blood pressure have any correlation to glucosereadings. FIG. 13C illustrates how many normal, approaching abnormal,and abnormal measurements were taken over a period of time. FIG. 13Dshows that additional information can be viewed when selecting aparticular set of values, in this case, the set of abnormalmeasurements. As shown, the user selected a particular time period, andwithin that time period, the user selected the abnormal readings. Thus,the device 102 displays the measurement data, such as value, date, time,or the like, associated with each abnormal reading in the set.

FIGS. 14A-14B illustrate exemplary calibration protocol interfaces.Particularly, FIG. 14A shows a user their progress through a calibrationprotocol, such as the protocol shown in FIG. 7 . In an embodiment, theinformation displayed may include time and date of last calibrations andnext calibrations, may include information on how many calibrations havebeen accomplished and/or how many remain. FIG. 14B illustrates how theapplications can guide a user through a calibration process. Forexample, a timeline may advantageously indicate where in a calibrationprocess the current measurements fall. Moreover, the timeline mayinclude days, months, and years tabs to quickly organize informationregarding device usage.

FIGS. 15A-15D illustrate exemplary alarm interfaces according toembodiments of the disclosure. In FIG. 15A, a measurement may indicatethat a user's glucose levels are low and may indicate an alarm by any ofplacing an icon, such as a bell, on the display, enclosing the displayin a red square, and/or highlighting on a trend graph the lowmeasurement. In some embodiments, the bell is placed low when theglucose levels are abnormally low, or high, when they are abnormallyhigh (FIG. 15B). Other more traditional visual and/or audio alarms mayalso be used including flashing display items or sounding audiblealarms, the intensity or frequency of which might vary to show severity.In FIG. 15B, a measurement may indicate that a user's glucose levels arehigh. In FIG. 15C, abnormally high measurements may trigger a message tosee a physician immediately, contact emergency services, check ketonelevels or the like. Moreover, additional icons, such as ringing multiplebells, or other icons may be used to show significant severity. In FIG.15D, a delta alarm may indicate the direction of change. For example, alow glucose level that is trend-wise dropping, indicates a moredangerous condition than one that is trend-wise raising. Icons and otherinformation may be highlighted to indicate these conditions.

FIGS. 16A-16C illustrate exemplary instructive interfaces, such as teststrip insertion guidance (FIG. 16A), general information about glucosemeasurements and glucose normality ranges (FIG. 16B), or pricinginformation for instrument usage (FIG. 16C). In FIG. 16A, theinstructive interface may also guide the user in calibrating orverifying strip reader measurements. For example, often strip readermanufacturers provide solutions for testing strip readers. The userdrips solution onto a test strip and inserts the strip into the reader.The solution is designed to cause the reader, when functioning properly,to provide a measurement within a provided range of acceptablemeasurements. These solutions will often include three bottlescorresponding to low, regular or medium and high solutions, designed tocause the reader to provide measurement in the low, medium and highranges. The interface may guide the user through, for example, usingthese solutions to verify accurate operation of the strip reader.

In FIG. 16C, the user may interact with the device to purchaseadditional spot checking credits. Spot checking accounting is disclosedin U.S. Pat. App. Pub. No. 2011-0172498, filed Jul. 14, 2011 titled“Spot Check Monitor Credit System,” incorporated by reference herein.

FIG. 17 illustrates an exemplary application interface showing, forexample, different types of medical and nonmedical applications thatmight be executed by the processing device 102. For example, theapplications may include noninvasive and minimally invasive glucosetesting, internet browsing, email, texting, video conferencing, cellularphone, graphs, activities or calendaring, flag or activity management,weather, photographs or videos, camera or video operation, calibrationprotocols, electronic interference detection, such as that disclosed inU.S. is disclosed in U.S. Pat. App. Pub. No. 2011-0109459, filed May 12,2011 titled “Interference Detector for Patient Monitor,” incorporated byreference herein, music, spot check purchasing applications, such asthose disclosed above, general questions and setting preferences,facebook, twitter, map or navigation, address book, internet bookmarks,downloadable applications of all sorts, and the like.

FIGS. 18A-18B illustrate an exemplary events interfaces including a foodflag interface. One application that may be extraordinarily helpful for,for example, a diabetic trying to manage their glucose levels is toinclude easily entered activities into a calendar program. Theseactivities or flags are associated with events such as fasting, insulin,food/drink intake, measurement, exercise, and the like. FIG. 18B showsan exemplary interface presented when the user wants to enter an eatingactivity. As shown, the information may include the amount ofcarbohydrates in the food, the portion or size, the glycemic index orthe like. As is understood by an artisan, the glycemic index includesranges of about fifty five (55) or less for most fruits and vegetables,legumes/pulses, whole grains, nuts, fructose and products low incarbohydrates, about fifty six (56) to about sixty nine (69) for wholewheat products, basmati rice, sweet potato, sucrose, baked potatoes, andabout seventy (70) or above for white bread, most white rices, cornflakes, extruded breakfast cereals, glucose, maltose.

FIGS. 19A-19B illustrate exemplary priority interfaces. As will bedisclosed in more detail below, certain applications will be designed totake a priority over other applications. In general, medicalapplications, such as those of FIG. 19A, will take priority over others,such as those of FIG. 19B. Moreover, in an embodiment, the order theicons appear within a figure may visually provide the user with anunderstanding of their priority. For example, in FIG. 19B, incomingphone activity takes priority over incoming email activity, etc. In anembodiment, the manufacturer sets the medical priorities over thenonmedical priorities. In an embodiment, the user may be able to addapplications to one or both priority interfaces to reorder defaultpriorities; however, the default priorities for certain applications maynot be editable to ensure safe operation of the device.

FIG. 20 illustrates a priority mode processing device having medicalrelated functions and non-medical related functions sharing commonresources. Advantageously, the processing device has a prioritymechanism so as to prevent the medical related functions from competingwith the non-medical related functions for the common resources duringcritical time periods. These critical time periods are indicated bytriggering events. In particular, a triggering event indicates to thesystem that the medical related functions have resource priority. Thispriority may be, for example, exclusive access to and use of displays,alarms, controls, communications and processing power so as to make timecritical patient health and risk assessments and output thoseassessments in a timely manner to a healthcare provider.

FIG. 21 illustrates a priority mode processing device embodiment havinga smart phone or other cellular communication device sharing one or morecommon resources with a processing device. The common resources mayinclude operating system functions, processor cycles and input/outputaccess, to name a few. A priority mode for the processing device may betriggered by the connection or disconnection of a device to the monitor,such as a sensor or sample, advantageously giving the monitor maximumaccess to processing and input/output resources so as to respond tophysiological data inputs and calculate medical parameters or conditionsaccordingly.

FIGS. 22A-22D are illustrations of priority mode glucometer embodiment.The glucometer is advantageously integrated in a handheld device havingboth processing device and smart phone capabilities. When a sensor ortest strip is plugged or inserted into the handheld device, it is usableas a glucometer. When the sensor or test strip is unplugged or removedfrom the handheld device, it is usable as a mobile phone, such as, forexample, a smart phone with many of today's smart phone applications andfunctions.

FIGS. 23-29 , described in detail below, illustrate various embodimentsthat combine processing device and smart phone features in anadvantageous manner so that the physiological measurements are notinterrupted or delayed by smart phone functions, such as incoming callsand text messages to name a few.

FIG. 23 illustrates processing device embodiment that utilizes a KVM(keyboard/video/mouse) switch for priority control. The KVM switchcontrols access to the display, touchscreen and audio between aprocessing device CPU that runs the medical system and a smart phone CPUthat runs the cell phone system.

FIG. 24 illustrates a processing device embodiment where the medicalfunctions are implemented as a single application running on the smartphone operating system (OS), such as those offered by Google (Android),Windows, Apple, or the like. In an embodiment, when a sensor or strip isplugged into the device, the OS activates the medical application andall other applications are suspended and cannot be resumed until thesensor/strip is unplugged or some other user supplied input is provided.

FIG. 25 illustrates a processing device embodiment where two separateoperating systems run as virtual machines on the device CPU. The cellphone OS handles cell phone functions and the medical OS handles themedical system functions.

FIG. 26 illustrates a processing device embodiment where the medicalapplication runs next to the cell phone OS (e.g. Android). As soon asthe sensor or strip is plugged into the device, the medical applicationis started and runs separate from the cell phone OS. The cell phone OSis suspended and the medical application takes control of the hardware,including the touch screen.

FIG. 27 illustrates a dual-boot processing device embodiment. As soon asa sensor or strip is plugged into the device, the cell-phone operatingsystem is shut down and the device is rebooted into the medicaloperating system.

FIG. 28 illustrates a double-sided processing device embodiment. A firstdisplay is mounted on one side of the device with cell-phonefunctionality and a second display is mounted on the other side of thedevice with medical functionality. A related embodiment implements twoseparate systems (cell-phone and medical) in one (hardware) chip, suchas a FPGA or ASIC.

FIG. 29 illustrates a processing device embodiment where the cell phoneas (e.g. Android) runs a single medical system application while asensor and/or strip is plugged into the device. When the sensor or stripis removed, the OS runs in a normal al operating mode, multitaskingvarious applications.

A priority mode processing device has been disclosed in detail inconnection with various embodiments. These embodiments are disclosed byway of examples only and are not to limit the scope of this disclosure.One of ordinary skill in art will appreciate many variations andmodifications.

In an embodiment, the features and functionality of the processingdevice 102 may be incorporated into smart phone technologies. Forexample, a smart phone may enables patients and healthcare personnel tomanage health data, and in particular, physiological reading data fromone or more health data collection devices such as a glucose sensor orpulse oximeter.

FIG. 30 illustrates an exploded view of a smart phone includinginternally integrated processing capability, such as, for example, aprocessing board or other device. As shown, the technology board 3000comprises an integrated board within the smart phone housing. The boardcommunicates with an external optical sensor, such as sensor 104. Invarious embodiments, the sensor provides an output signal indicative ofan amount of attenuation of predetermined wavelengths (ranges ofwavelengths) of light by body tissues, such as, for example, a digit,portions of the nose or ear, a foot, or the like. The predeterminedwavelengths often correspond to specific physiological data desired,including for example, blood oxygen information such as SpO2, bloodglucose, total hemoglobin, methemoglobin, carboxyhemoglobin, bulk tissueproperty measurements, water content, pH, blood pressure, respirationrelated information, cardiac information, indications of perfusion, orthe like. The smart phone may also include software such as anapplication configured to manage output measurement data from theprocessing board. The application functionality can include trendanalysis, current measurement information, alarms associated with belowthreshold readings or reminders to take measurement data at certaintimes or cycles, display customization, iconic data such as heartsbeating, color coordination, bar graphs, gas bars, charts, graphs, orthe like, all usable by a caregiver or smart phone user to enablehelpful and directed medical monitoring of specified physiologicalparameters.

The smart phone may advantageously be capable of connecting to andreceiving data from a physiological data collection device such as anoptical sensor glucose sensor. The smart phone is able to connect to adata collection device and receive data from the device. The smart phonemay be configured to analyze data from the device, display data from thedevice, and otherwise utilize the data to empower the user to takecontrol of his health.

The smart phone may have a fully integrated technology board whichreceives and analyzes data from the collection device. The technologyboard may alternatively be housed within a removable cartridge. Theboard may employ RF shielding. The smart phone may utilize a Samsung GHzprocessor or the like. The processor may utilize mDDR2 or mDDR, or thelike. In some embodiments, the processor may employ MLC NAND 48 TSSOPflash memory technology or the like. The smart phone may comprise apower management integrated circuit with on/off/wakeup capability.

In an embodiment, the smart phone may utilize one of a number ofdifferent operating systems. For example, an android, linux, or qnxsystem may be used.

Software may be installed upon the smart phone that can analyze the datareceived from the sensor device and make it available in a way for theuser to manage his health. There may be software which allows a user toview the data in a multitude of ways. The smart phone may also be ableto alert the user to an abnormal data reading. The software may alsoalert the user to take a physiological reading or medication. It mayhave the capability of sending physiological data to a home computerwhere the user manages his health data. The data can also be sent to aphysician or pharmacist for their expertise and feedback.

The smart phone through the board may include an input that can connectto the data collection device or optical sensor. In some embodimentsthis sensor may be on the top portion of the smart phone, integratedinto the smart phone housing or housing attachment, or a separateddevice as shown. The connector may be chosen from a variety ofconnectors including a snap click connector, a magnetic connector and/ora multi pin connector. In some embodiments, the smart phone may comprisea magnetic latch sensor port with dual orientation with allows for acontrolled break away. In an embodiment, the sensor includes activepulse technology designed to provide a perturbation of the tissue duringmeasurements.

The smart phone may have a display that is between about 3″ and about 5″or more. A bigger screen may advantageously allow more versatility froma user experience perspective. The display may have the capability ofswitching between a portrait and a landscape mode based on userpreference or automatically based on positioning. The display, in someembodiments, has a wide viewing angle in both portrait and landscapemode. It may have a backlight in one of both of the modes. In someembodiments, the resolution is around about 960×640 with a 24 bit rate.

The display may be a projective capacitive LCD screen. The screen may bemade from impact resistant materials such as gorilla glass®, sapphirecrystal or polycarbonate. The conductive coating may be made of avariety of materials including indium tin oxide (ITO). The screen may bea multi input screen with 3 or more inputs. The screen may also supportgestures such as an x/y swipe inertia scroll, presshold, 2 point pinchzoom, 3 point pinch zoom and swiping. In some embodiments, the smartphone is capable of utilizing haptic technology to communicate with theuser. This feature may be useful to alert a user to significant changesin physiological measurements. The device may also utilize a bezel tomaneuver around the display.

The smart phone may comprise a power button. The button may be a tactilebutton that produces an audible click. The button may be located on aside of the smart phone.

The smart phone may include a chargeable battery to provide power to thedevice. In some embodiments, the battery may be a 1500-3000 mAh lithiumbattery. The battery may be housed in a recess of the smart phonecovered by a removeable battery door. This may be located on the back ofthe phone.

The smart phone may additionally comprise an AC power input. In someembodiments, the input is located on a side of the device.Alternatively, the device may be inductively charged.

The smart phone may also comprise one or more USB ports. The ports maybe regular or micro USB ports. The ports may utilize a USB switch suchas a Fairchild switch. The USB port may be capable of charger detection,audio and UART detection. The USB ports may be located on a side of thesmart phone.

The smart phone may be capable of wireless communication. This may beachieved through a wireless connection such as a Broadcom 802.11 a/b/g/ndual band connection. It may also utilize a Bluetooth connection, an FMreceiver using an RDS standard, or the like. The smart phone may alsocomprise a module to allow for connectivity to networks such as the 3Gnetwork, 4G network, and the like.

The smart phone may contain a speaker and/or an earphone jack located onit. In some embodiments, the speaker is a multi-directional speaker foraudio over air. The speaker may be capable of 85 db. The smart phone mayfurther comprise an amplifier. The amplifier may be a 3 W filter-freeclass D mono audio amplifier in some embodiments. A volume control maybe located on the phone. In some embodiments, the volume control may bea volume rocker switch.

The smart phone may comprise a camera. The camera may be a video and/orstill camera. The smart phone may contain a camera on the front side andrear side of the phone to enable things like self-portraits and videochats. In some embodiments, the front camera is a 1.3 MP camera. In someembodiments, the back camera is an 8 MP camera. The camera(s) may alsocomprise a flash which may be an LED flash.

Some or all of the part of the device not making up the screen may becomprised of a variety of materials including liquid metal, CNCaluminum, and Hydro Formed aluminum. Soft touch paint may be applied.

The smart phone may comprise high durometer bumper fins to protect itfrom drops and everyday wear and tear. The fins may comprise a materialthat is not temperature sensitive, has a generally high chemicalresistance, is flexible, and is durable. In some embodiments, thismaterial may be multi-shot santoprene or another thermoplasticelastomer. The fins may be located on the rear side of the smart phone,at the top and bottom of the device. There may be between 1 and 5 finslocated on both the right and left sides of the smart phone. The finsmay extend towards the top of the device and wrap around to cover aportion of the top of the device. The bottom fins may be designed in asimilar manner.

The foregoing features are not intended to be exhaustive. The smartphone may contain additional features such as an acoustic speaker slot,a slot for Micro SD, HDMI outputs, a microphone, a sim card draw, anaccelerometer and the like.

FIG. 31 illustrates insertable cartridges that may connect to, forexample, a technology board or other interface on a general purposesmart phone. As shown in FIG. 31 , the insertable cartridge may befunction specific. It could be a glucose sensor cable cartridge. Aglucose sensor may be integrated into the cartridge. The cartridge couldalternatively be a temperature and blood pressure cartridge. Thecartridge may be an environmental sensor, for instance, measuring CO inparts/million. It may be an extra battery cartridge. The cartridge maybe a barcode scanner or other digital device interface for data import,software, application firmware upgrades or patient management. Thecartridge could also provide general oximetry or cooximetryfunctionality and sensor connectivity, or may be acoustic sensorcompliant and determine respiration parameters.

The smart phone device described may advantageously allow a user tocarry only one unit rather than both a phone and a sensor device. As aresult of its dual functionality, the device may be bigger and morecostly than a traditional smart phone. Additionally a user may have toreplace their existing phone. Another advantage is that the smart phoneto be used as an con the go′ health organizers. This setup also allowsthe user more technology options. For example, glucose readings as wellas pulse oximetry readings may be received by the smart phone device. Itis also easier to input information using the smart phone device,particularly when the user has to re-calibrate the device on a weeklybasis.

In another embodiment of the smart phone device, the technology boardwith the integrated data collection device may be a separate unit fromthe smart phone. In FIGS. 31-34 , the smart phone may include a wirelesschipset (FIG. 32 ) that communicates with stand-alone data collectiondevices (FIG. 33-34 ). The stand-alone devices may provide functionalitysimilar to any individual or combination of the cartridges mentioned inthe foregoing. The wireless chipset my provide UWB, Bluetooth, Zigbee,and wireless USB connectivity.

The stand-alone units provide for smaller more portable smart phones,Additionally, the user has the option to carry the smart phone andsensor device together or separately, which could be less cumbersome. Insome embodiments, the units may include a display. The unit maycommunicate with a smart phone to better present measurementinformation, processed information, and/or trend information to a useron more advanced smart phone displays. The unit may be capable ofwireless communication with any mobile phone or computer. The unit willneed to be able to connect to an external computing device in order tocalibrate.

One significant advantage of the smart phone embodiments is that thesmart phone manufacturers, and not the medical device manufacturer, hasinvested the resources into developing and commercializing theprocessing used for nonmedical applications. Development of thishardware and software is thus lifted from a medical device focusedcompany.

Although the foregoing processing device and smart phones have beendescribed in terms of certain preferred embodiments, other embodimentswill be apparent to those of ordinary skill in the art from thedisclosure herein. For example, alternate protocols may be implementedor the like. Additionally, other combinations, omissions, substitutionsand modifications will be apparent to the skilled artisan in view of thedisclosure herein. Accordingly, the present invention is not intended tobe limited by the reaction of the preferred embodiments, but is to bedefined by reference to the appended claims.

All publications, patents, and patent applications mentioned in thisspecification are herein incorporated by reference to the same extent asif each individual publication, patent, or patent application wasspecifically and individually indicated to be incorporated by reference.

Moreover, terms used herein are intended to have their broad ordinarymeaning understood within the art. The term “and/or” in intended to meanthat one, any combination of two or more, or all combinations of thecorresponding listed elements are appropriate; however, it is notintended to mean that all combinations must be accomplished.

What is claimed is:
 1. A local health monitoring device configured toprovide a wearer measurement values of a plurality of physiologicalparameters of the wearer determined using absorption-derived data andrepeatedly updated user-specific calibration data, the local healthmonitor device comprising: a display; at least one local processor, saidlocal processor operably communicating with one or more noninvasivesensors configured to output sensor signals responsive to a pulse rateof the wearer based on detection of attenuated light by said noninvasivesensor, said at least one local processor receiving said output sensorsignals and configured to determine first measurement values of saidpulse rate using wearer-specific calibration data; said local processorconfigured to operably communicate with a remote server operablycommunicating with remote memory, said remote memory geographicallyremote from said wearer, said remote memory configured to store saidfirst measurement values of said pulse rate and other measurement valuesnot associated with said wearer, said remote server configured processsaid first measurement values and said other measurement values todetermine an updated wearer-specific calibration data, said updatedwearer-specific calibration data responsive to at least relationshipsbetween noninvasive measurements and clinically-determined outputmeasurements of one or more physiological parameters, said at least onelocal processor configured to receive said updated wearer-specificcalibration data from said remote server and configured to determinesecond measurement values of said pulse rate using said updatedwearer-specific calibration data; and said display providing displayindicia to said wearer, said indicia responsive to said first or secondmeasurement values of said pulse rate.
 2. The local health monitoringdevice of claim 1, further comprising an ECG sensor.
 3. The local healthmonitoring device of claim 1, further comprising a temperature sensor.4. The local health monitoring device of claim 1, further comprising aacoustic sensor.
 5. The local health monitoring device of claim 1,further comprising a respiration sensor.
 6. The local health monitoringdevice of claim 1, further comprising a sleep apnea sensor.
 7. The localhealth monitoring device of claim 1, further comprising a depth ofconsciousness sensor.
 8. The local health monitoring device of claim 1,when said local processor operably communicates with said remote serverto upload said first measurement values, said upload includes onlydeidentifying information.